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Augmenting service recommender systems by incorporating contextual opinions from user reviews

Research article (User Modeling and User-Adapted Interaction, 2015) · cited 57× · AI/ML
academia openalex:W2125072293
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Augmenting service recommender systems by incorporating contextual opinions from user reviews

Summary

Augmenting service recommender systems by incorporating contextual opinions from user reviews is a scholarly article[1].

Key Facts

  • Augmenting service recommender systems by incorporating contextual opinions from user reviews's instance of is recorded as scholarly article[2].

References

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Direct Wikidata claims

  1. [2] ↑ . wikidata.org.

Class ancestry

  1. [1] ↑ . Wikidata. wikidata.org.

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APA 4ort.xyz Knowledge Graph. (2026). Augmenting service recommender systems by incorporating contextual opinions from user reviews. Retrieved May 24, 2026, from https://4ort.xyz/entity/augmenting-service-recommender-systems-by-incorporating-contextual-opinions-from-user-reviews
MLA “Augmenting service recommender systems by incorporating contextual opinions from user reviews.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/augmenting-service-recommender-systems-by-incorporating-contextual-opinions-from-user-reviews.
BibTeX @misc{4ortxyz_augmenting-service-recommender-systems-by-incorporating-contextual-opinions-from-user-reviews_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Augmenting service recommender systems by incorporating contextual opinions from user reviews}}, year = {2026}, url = {https://4ort.xyz/entity/augmenting-service-recommender-systems-by-incorporating-contextual-opinions-from-user-reviews}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Augmenting service recommender systems by incorporating contextual opinions from user reviews — https://4ort.xyz/entity/augmenting-service-recommender-systems-by-incorporating-contextual-opinions-from-user-reviews (retrieved 2026-05-24)

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